Schema and AI Overviews: Does Structured Data Improve Visibility?

Google’s AI Overviews are becoming a key real estate for brands looking to stand out in search. But one question keeps popping up in the SEO world: Does structured data (schema) actually improve your chances of being cited in an AI Overview?

A recent experiment suggests that the quality of schema—not just its presence—may influence AI Overview visibility.

Why Schema Matters for AI Visibility

Schema was designed to make web content more machine-readable. Search engines and even large language models use it to better interpret page context, freshness, and relevance. That’s why many marketers assume schema could play a role in helping content surface in AI-powered search features.

The Experiment Setup: Three Pages, Three Approaches

In this test, researchers built three single-page websites that were nearly identical in every way—content, keywords, and technical setup—except for one key difference: the use of schema.

• Page 1: Strong, well-implemented schema
• Page 2: Poorly implemented schema (errors and missing fields)
• Page 3: No schema at all

To ensure fairness, the pages targeted carefully selected keywords that consistently triggered AI Overviews. Once published, all three were submitted to Google for indexing to compare how they would rank and whether any would appear in AI Overviews.

The Results: Schema Quality Made a Difference

Here’s what happened:

• Well-implemented schema page: Appeared in an AI Overview and ranked as high as Position 3 for multiple keywords.
• Poor schema page: Ranked for several keywords but never surfaced in an AI Overview.
• No schema page: Crawled but not indexed, meaning no rankings and no AI Overview presence.

The takeaway? Only the page with properly implemented schema earned AI Overview visibility.

Methodology: How the Test Was Controlled

In this experiment, researchers worked to eliminate other ranking factors so that schema quality could be isolated as the key variable.

• Keywords: All test pages targeted keywords with similar difficulty and low search volume (around 60 searches per month).
• Page structure: Each was built as a single-page site with no JavaScript, no sitemap, no robots.txt, and no canonical tags.
• Schema differences only: The variable across the three sites was schema implementation—one with strong schema, one with errors, and one with none.

The “good schema” page included elements such as:

• Complete Article schema with required fields
• FAQ schema for relevant questions
• Breadcrumb navigation schema
• Correct date formatting
• Author and publisher details
• Audience targeting and related topics

By contrast, the “poor schema” page was missing key fields, had misformatted data, and lacked supporting schema types.

Suggestions for SEO and AI Overviews

While the test was limited in scope, the results pointed toward a meaningful trend:

• Well-implemented schema was associated with greater visibility.
• Pages without schema struggled to gain traction.
• Poorly implemented schema provided some benefit, but not nearly as much as properly structured data.

In short, clean and comprehensive schema may give pages a competitive edge in Google’s AI Overviews and traditional rankings.

What’s Next?

These findings are promising but not conclusive. More testing is needed to confirm whether schema directly drives AI Overview presence. Follow-up experiments are expected to involve swapping schema across otherwise identical pages to see if results can be replicated.

Understanding how schema impacts AI visibility is just one part of modern SEO.
At Earn SEO, an experienced SEO agency in New York, we help businesses implement strategies that improve search rankings and enhance AI-driven presence. From structured data to full-scale optimization, our team ensures your website is seen by the right audience.

Ready to take your SEO to the next level? Partner with us today and turn insights into results.